Monte Carlo Simulation: Stochastic uncertainty propagation through MCDM model

Overview

Robustness wrapper: Monte Carlo uncertainty propagation. Output typically robustness_score (higher value = preferred).

Strengths

• •Method-specific: Robustness wrapper: Monte Carlo uncertainty propagation

Limitations

• •Assumes: A base ranking method is selected
• •Assumes: Computational budget for repeated runs

Assumptions to verify

• •A base ranking method is selected
• •Computational budget for repeated runs

When not to use

• •Quick analysis needed → defer robustness check

Edge cases

• •See F.steps and D.parameters for MONTE-CARLO-SIMULATION-specific edge handling. recommendation_metadata.assumptions_to_verify also lists boundary conditions.

Common pitfalls

• •Hatalı: 'MONTE-CARLO-SIMULATION bu varsayımı kontrol etmeden uygulamak'. Doğrusu: A base ranking method is selected
• •Hatalı: 'MONTE-CARLO-SIMULATION bu varsayımı kontrol etmeden uygulamak'. Doğrusu: Computational budget for repeated runs
• •Hatalı: MONTE-CARLO-SIMULATION'yi 'Quick analysis needed → defer robustness check' durumunda kullanmak: recommendation_metadata.not_recommended_when alternatif öneriyor.

Worked example

1. 1.Adım 1 (F1): Validate inputs for monte-carlo-simulation. Formül: \hat{r}_i=\frac{1}{N}\sum_{k=1}^N\mathbf{1}[\text{rank}_i^{(k)}=r]\ \forall r\ (\text{rank acceptability index}) Anchor: Metropolis 1949, (pending PDF page verification)

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